Preservation Communities

From Earth Science Information Partners (ESIP)

Back to Preservation and Stewardship

Data Stewardship Principles breaks this down into:

  1. Data Creators (field experiment projects, research or operational missions, aircraft campaigns, etc.)
  2. Data Intermediaries (repositories, value-added providers, etc.)
  3. Data Users

We can further sub-divide those categories:

  1. Data Creators [In one sense we could divide this into classes--those who collect observations (in situ or remote sensed) and those who create derivations (through algorithms or models or aggregations)]
    1. subcommunities as biodiversity samplers, aerial survey mappers, climatology builders using in situ data, and so on
    2. Project managers responsible for instruments or software
  2. Data Intermediaries
    1. Data center personnel, including administrators, operations staff
    2. Data managers "embedded" in data creation efforts
    3. Information designers and product developers
  3. Data Users [Doesn't NASA already have a classification of about a dozen data user types?]
    1. Disciplinary Earth science researchers, perhaps broken into such subcommunities as climate modelers, statistical climate researchers, oceanic chemists, soil hyrdologists, and so on
    2. Government agency managers, such as watershed managers, EPA or CDC environmental monitors or regulators
    3. Federal agency funding managers
    4. Students
      1. K-6
      2. 7-12
      3. college
      4. graduate student

The US Census Bureau has population projections, as well as educational achievement and other interesting information that can help quantify the potential user communities. See for population projections (out to 2060). See and related sites for information on educational sites.

For each of these categories, it would be very helpful to have a concept map that represents what kind of concepts they might be familiar with. For students, we could pull concepts from the state and national educational standards list, perhaps with some help from the educational cluster. It might also be helpful to categorize the concepts by skill level. For example, mathematical proficiency, with some gradation, such as

  1. Can do pencil and paper exercises
  2. Can use simple tools or spreadsheets to do calculations
  3. Can program simple algorithms
  4. Can understand and program error analyses.